Method for Attaining Caraway Seed Oil Fractions with Different Composition
Bibliographic record
Abstract
Caraway (Carum carvi L.) is a medicinal and aromatic plant; its seeds (fruits) are used as spice and they contain essential oils. We hypothesized that by collecting caraway oil at different time points during the extraction process, we could obtain oil fractions with distinct chemical composition. A hydrodistillation time (HDT) study was conducted to test the hypothesis. The caraway seed oil fractions were collected at eight different HDT (at 0 - 2, 2 - 7, 7 - 15, 15 - 30, 30 - 45, 45 - 75, 75 - 105, and 105 - 135 min). Additionally, a non-stop HD for 135 min was conducted as a control. Most of the oil was eluted early in the HD process. The non-stop HDT treatment yielded 2.76% oil by weight. Of the 24 essential oil constituents, limonene (77 - 19% of the total oil) and carvone (20 - 79%) were the major ones. Other constituents included myrcene (0.72 - 0.16%), trans-carveol (0.07 - 0.39%), and β-caryophyllene (0.07 - 0.24%). Caraway seed oil with higher concentration of limonene can be obtained by sampling oil fractions early in HD process; conversely, oil with high concentration of carvone can be obtained by excluding the fractions eluted early in the HD process. We demonstrated a method of obtaining caraway seed oil fractions with various and unique composition. These novel oil fractions with unique composition are not commercially available and could have much wider potential uses, and also target different markets compared to the typical caraway essential oil.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".